---
title: "Hire Argo Workflows Engineers for Kubernetes Pipelines"
description: "Argo Workflows engineers run container steps as Kubernetes pipelines with firm control of resources. Hire them as a dedicated, managed offshore team."
url: "https://azendo.co/skills/argo-workflows/"
---

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3. Argo Workflows

# Argo Workflows specialists for your dedicated team.

Argo Workflows is a Kubernetes-native workflow engine where each step runs as a container in a DAG. It is used for machine learning pipelines, data processing and any multi-step containerised job.

## Where Argo Workflows fits in a long-term product team.

Running every step as a container means each can have its own image, dependencies and resource request. A pipeline with a Python preprocessing step, a GPU training step and a Go evaluation step is natural here, where an orchestrator assuming one runtime makes it awkward.

Per-step resource specification is the practical advantage in machine learning. Requesting a GPU only for the step that needs it means paying for an accelerator during training, with no cost during a data download.

## What your dedicated team does with Argo Workflows.

It assumes Kubernetes fluency. Debugging means reading pod logs and events, and a team without that experience finds failures opaque in a way a managed orchestrator would not be.

Whether that trade is right depends on whether the cluster is already part of the estate, assessed at scoping alongside a [dedicated cloud and DevOps team](https://azendo.co/services/dedicated-cloud-and-devops-team/).

## Common Argo Workflows use cases.

* Steps with different runtimes Each stage in its own image.
* GPU requested only where needed Per-step resources, so accelerators are not held during data movement.
* Pipelines beside the workloads One cluster and one set of tooling for training and serving.

## Adding Argo Workflows skills to your team.

Kubernetes-native pipelines are assigned across AI and platform capacity, with cluster fluency treated as a prerequisite.

Argo Workflows specialists join your team remotely as dedicated, full-time team members, selected, employed and managed by us in Chiang Mai and Bangkok. Companies that [hire offshore developers](https://azendo.co/hire-a-dedicated-development-team-in-thailand/) through Azendo add the skill when the product calls for it.

## Roles that use Argo Workflows

* [ML Platform Engineer MLOps engineering](https://azendo.co/services/dedicated-mlops-team/ml-platform-engineer/)
* [MLOps Engineer MLOps engineering](https://azendo.co/services/dedicated-mlops-team/mlops-engineer/)

## Service areas that use Argo Workflows

* [MLOps engineering](https://azendo.co/services/dedicated-mlops-team/)

Capacity is agreed across your whole team, with one monthly fee, not per skill.

## Related in mlops and model delivery

* [MLOps handoff, a skill in our teams](https://azendo.co/skills/mlops-handoff/)
* [ONNX, a skill in our teams](https://azendo.co/skills/onnx/)
* [TensorRT, a skill in our teams](https://azendo.co/skills/tensorrt/)
* [Model registry, a skill in our teams](https://azendo.co/skills/model-registry/)
* [Weights & Biases, a skill in our teams](https://azendo.co/skills/weights-and-biases/)
* [Comet, a skill in our teams](https://azendo.co/skills/comet/)
* [Neptune.ai, a skill in our teams](https://azendo.co/skills/neptune-ai/)
* [DVC, a skill in our teams](https://azendo.co/skills/dvc/)

## Tell us what you need Argo Workflows for.

A service delivery manager will reply with the specialists we'd suggest, the monthly capacity and what the first month looks like.

[Browse all skills](https://azendo.co/skills/)